The research of the Multimodal Medical Imaging Optimization (MMIO) Lab focuses on leveraging the advances in artificial intelligence (AI) and multimodal medical imaging to optimize the reconstruction and quantification of positron emission tomography (PET). Through the injection of radiolabeled tracers, PET allows for the accurate localization and quantification of metabolic processes in the imaged subject. AI and multimodal imaging will aid PET in overcoming its inherent physical and hardware limitations for an increased nominal resolution, more accurate quantification, and flexibility in clinical scanning protocols. Building upon the PI (Dr. Kevin T. Chen)'s previous research in the use of optimized PET data on neuroimaging, we aim to further investigate the potential that optimized multimodal imaging brings to enhance the understanding, diagnosis, and eventual treatment of diseases such as dementia.

2025/2 Congratulations to Yu-Nong for having her article accepted at the IEEE Transactions on Radiation and Plasma Medical Sciences!

2025/2 Welcome Yu-Ju to the lab!

2024/7 Congratulations to Cheng-Han, Yu-Nong, and Cheng-Yu for successfully defending their master's theses!

2024/4 Dr. Chen has been selected as a Young Scholar of the Asia Pacific Biomedical Engineering Consortium!